this determines the "starting" lambda for a sequence of values for
softImpute, and all nonzero solutions would require a smaller
value for lambda.

Usage

1

Arguments

x

An m by n matrix. Large matrices can be in "sparseMatrix" format, as
well as "SparseplusLowRank". The latter arise after centering sparse
matrices, for example with biScale, as well as in applications
such as softImpute.

The remaining arguments only apply to matrices x in
"sparseMatrix", "Incomplete", or "SparseplusLowRank" format.

lambda

As in svd.als, using a value for lambda can speed up
iterations. As long as the solution is not zero, the value returned
adds back this value.

maxit

maximum number of iterations.

trace.it

with trace.it=TRUE, convergence progress is reported.

thresh

convergence threshold, measured as the relative changed in the Frobenius
norm between two successive estimates.

Details

It is the largest singular value for the matrix,
with zeros replacing missing values. It uses svd.als with
rank=2.